title: Development of conductive polymer analysis for the rapid detection and identification of phytopathogenic microbes.
abstract: ABSTRACT Conductive polymer analysis, a type of electronic aroma detection technology, was evaluated for its efficacy in the detection, identification, and discrimination of plant-pathogenic microorganisms on standardized media and in diseased plant tissues. The method is based on the acquisition of a diagnostic electronic fingerprint derived from multisensor responses to distinct mixtures of volatile metabolites released into sampled headspace. Protocols were established to apply this technology specifically to plant disease diagnosis. This involved development of standardized cultural methods, new instrument architecture for sampling, sample preparation, prerun procedures, run parameters and schedules, recognition files and libraries, data manipulations, and validation protocols for interpretations of results. The collective output from a 32-sensor array produced unique electronic aroma signature patterns diagnostic of individual microbial species in culture and specific pathogen-host combinations associated with diseased plants. The level of discrimination applied in identifications of unknowns was regulated by confidence level and sensitivity settings during construction of application-specific reference libraries for each category of microbe or microbe-host combination identified. Applications of this technology were demonstrated for the diagnosis of specific disease systems, including bacterial and fungal diseases and decays of trees; for host identifications; and for determinations of levels of infection and relatedness between microbial species. Other potential applications to plant pathology are discussed with some advantages and limitations for each type of diagnostic application.
authors.forename: A D
authors.initials: AD
authors.lastname: Wilson
authors.forename: D G
authors.initials: DG
authors.lastname: Lester
authors.forename: C S
authors.initials: CS
authors.lastname: Oberle